from numpy import dot,array,empty_like
from matplotlib.path import Path
def make_path(x1,y1,x2,y2):
return Path([[x1,y1],[x1,y2],[x2,y2],[x2,y1]])
def perp( a ) :
b = empty_like(a)
b[0] = -a[1]
This file contains bidirectional Unicode text that may be interpreted or compiled differently than what appears below. To review, open the file in an editor that reveals hidden Unicode characters.
Learn more about bidirectional Unicode characters
""" | |
Grammar: | |
======== | |
Expression --> AndTerm { OR AndTerm}+ | |
AndTerm --> Condition { AND Condition}+ | |
Condition --> Terminal (>,<,>=,<=,==) Terminal | (Expression) | |
Terminal --> Number or String or Variable | |
Usage: | |
====== |
This file contains bidirectional Unicode text that may be interpreted or compiled differently than what appears below. To review, open the file in an editor that reveals hidden Unicode characters.
Learn more about bidirectional Unicode characters
#!/bin/sh | |
# check for how many uncommitted changes we have | |
# stash changes | |
# run grunt task | |
# restore stashed files if anything was stashed | |
# exit with error if grunt fails | |
NAME=$(git branch | grep '*' | sed 's/* //') |
This file contains bidirectional Unicode text that may be interpreted or compiled differently than what appears below. To review, open the file in an editor that reveals hidden Unicode characters.
Learn more about bidirectional Unicode characters
from collections import defaultdict, deque | |
class Graph(object): | |
def __init__(self): | |
self.nodes = set() | |
self.edges = defaultdict(list) | |
self.distances = {} | |
def add_node(self, value): |
Hi there! Since this post was originally written, nvm
has gained some new tools, and some people have suggested alternative (and potentially better) approaches for modern systems. Make sure to have a look at the comments to this article, before following this guide!
Trickier than it seems.
This file contains bidirectional Unicode text that may be interpreted or compiled differently than what appears below. To review, open the file in an editor that reveals hidden Unicode characters.
Learn more about bidirectional Unicode characters
plugins: | |
... | |
- convertDimensions | |
... |
This file contains bidirectional Unicode text that may be interpreted or compiled differently than what appears below. To review, open the file in an editor that reveals hidden Unicode characters.
Learn more about bidirectional Unicode characters
import torch | |
from collections import OrderedDict | |
def rename_state_dict_keys(source, key_transformation, target=None): | |
""" | |
source -> Path to the saved state dict. | |
key_transformation -> Function that accepts the old key names of the state | |
dict as the only argument and returns the new key name. | |
target (optional) -> Path at which the new state dict should be saved |
This file contains bidirectional Unicode text that may be interpreted or compiled differently than what appears below. To review, open the file in an editor that reveals hidden Unicode characters.
Learn more about bidirectional Unicode characters
import sympy as sym | |
import numpy as np | |
import matplotlib.pyplot as plt | |
sym.init_printing() | |
# Integral calculation constants | |
a = 0 | |
b = 20 | |
h = 0.4 |
OlderNewer